CRCYHCJan 13

Chatting with Confidants or Corporations? Privacy Management with AI Companions

arXiv:2601.10754
AI Analysis

For researchers and designers of AI companions, this work extends privacy theory to human-AI relationships, revealing unique tensions between emotional intimacy and institutional risks.

This study investigates how users of AI companion chatbots (e.g., Replika, Character.AI) manage privacy, finding that they blend interpersonal trust with institutional awareness but often feel powerless over platform-level data control, leading to privacy turbulence.

AI chatbots designed as emotional companions blur the boundaries between interpersonal intimacy and institutional software, creating a complex, multi-dimensional privacy environment. Drawing on Communication Privacy Management theory and Masur's horizontal (user-AI) and vertical (user-platform) privacy framework, we conducted in-depth interviews with fifteen users of companion AI platforms such as Replika and Character.AI. Our findings reveal that users blend interpersonal habits with institutional awareness: while the non-judgmental, always-available nature of chatbots fosters emotional safety and encourages self-disclosure, users remain mindful of institutional risks and actively manage privacy through layered strategies and selective sharing. Despite this, many feel uncertain or powerless regarding platform-level data control. Anthropomorphic design further blurs privacy boundaries, sometimes leading to unintentional oversharing and privacy turbulence. These results extend privacy theory by highlighting the unique interplay of emotional and institutional privacy management in human-AI companionship.

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